What is Arellano Bond serial correlation test?
The Arellano–Bond test is a test of correlation based on the residuals of the estimation. By default, the computation is done with the standard covariance matrix of the coefficients. A robust estimator of this covariance matrix can be supplied with the vcov argument.
What is the difference between Xtabond and xtabond2?
To compensate, xtabond2, unlike xtabond, makes available a finite-sample correction to the two-step covariance matrix derived by Windmeijer (2000). This can make twostep robust more efficient than onestep robust, especially for system GMM.
What is System GMM estimation?
The system GMM estimator in dynamic panel data models combines moment conditions for the differenced equation with moment conditions for the model in levels. An initial optimal weight matrix under homoskedasticity and non-serial correlation is not known for this estimation procedure.
How do you test for Overidentifying restrictions?
This can be done using the corresponding F -statistic by computing J=mF. J = m F . This test is the overidentifying restrictions test and the statistic is called the J -statistic with J∼χ2m−k J ∼ χ m − k 2 in large samples under the null and the assumption of homoskedasticity.
What is Overidentifying restrictions test?
The overidentifying restrictions test (also called the J -test) is an approach to test the hypothesis that additional instruments are exogenous. For the J -test to be applicable there need to be more instruments than endogenous regressors.
What is xtabond2?
Description. xtabond2 can fit two closely related dynamic panel data models. The first is the Arellano-Bond (1991) estimator, which is also available with xtabond, though without the two-step standard error correction described below. It is sometimes called “difference GMM.”
Why is GMM used?
GMM generalizes the method of moments (MM) by allowing the number of moment conditions to be greater than the number of parameters. Using these extra moment conditions makes GMM more efficient than MM.
What is GMM estimation?
The generalized method of moments (GMM) is a statistical method that combines observed economic data with the information in population moment conditions to produce estimates of the unknown parameters of this economic model.
What is the difference between difference GMM and system GMM?
Difference GMM is so-called because estimation proceeds after first-differencing the data in order to eliminate the fixed effects. System GMM augments Difference GMM by estimating simultaneously in differences and levels, the two equations being distinctly instrumented.
How do you calculate GMM?
The first step is to estimate the GMM parameter vector ˆθ1,GMM using the simple identity matrix as the weighting matrix W=I. The optimal weighting matrix is the inverse of the two-step variance covariance matrix. Lastly, re-estimate the GMM estimator using the optimal two-step weighting matrix.
What is GMM system?
The GMM-SYS estimator is a system that contains both the levels and the first difference equations. It provides an alternative to the standard first difference GMM estimator.
Why do we use system GMM?